Bayesian design of experiment (B-DOE) uses the principle of Bayesian Epistemology that explain the evidence as a logical-probalistic coherence on the basis of rational degrees of belief (or degrees of confidence). The researcher has design the (B-DOE) using Multilevel Hierarchy (MH), and data that may be obtained at the weak to moderate evidence level (literature, biological. Mechanism, computational and retrospective) may be helpful to identify bioactive compounds for treating (CMT) and provide the knowledge on pathogenesis, prognostic of the disease and collective mechanism of drug of action. The investigators will classify the evidence on the basis of hierarchy as moderate and weak, which will ultimately help to study new promising bioactive compounds potentially able to solve some of the issues related to CMT.
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Charcot-Marie-Tooth (CMT) is often misdiagnosed inherited neuromuscular disease discovered by three French doctors, Jean-Marie Charcot, Pierre Marie, and Howard Henry Tooth, in 1886. The study of CMT disease was presented by Dr. Frerick Peterson in 1899 as rare disorder with muscles loss of the extremities, muscular atrophy of legs below the knees and arms below the elbows (Peterson, 1899) and loss of sensitivity (Harding & Thomas, 1980). A family history of Charcot-Marie-Tooth disease increased the probability to 91% (Nagai et al., 2006). CMT has been classified into demyelinating and axonal forms (CMT 2). CMT 1 is classified as demyelinating autosomal dominant, CMT 4 is classified as demyelinating autosomal recessive. The disease has been sub-classified based upon causative gene (Pareyson & Marchesi, 2009).
The prevalence of genetically confirmed CMT patient in Korea in 2018 was 5.2 per 100,000 persons (Park et al., 2020). With four times increase in the incidence of CMT disease (1988-2012), the prevalence of CMT disease in Norway was 22.5 per 100000 (Vaeth et al., 2017). Age-standardized point prevalence of all CMT cases was 15.7 per 100 000 in Auckland, New Zealand (NZ) (Theadom et al., 2019). A recent study in Germany has identified a substantial economic burden of CMT neuropathy and estimated total annual cost of illness of $22,362 per patient, of which 67.3% were direct costs (Schorling et al., 2019). A study on 407 registered patients has mentioned the impact CMT disease on ankle weakness (99.7%), loss of balance (98.6%), mobility issue (97.5%) and finger and hand weakness (97%) (Johnson et al., 2014). Neuropathic pain, nociceptive pain and non-painful sensory symptoms is associated with CMT disease and have an impact in affecting the patient's quality of life (Gemignani et al., 2004).
Drug development is a time-consuming, labour-intensive, expensive, and risky operation. A systematic review from thirteen (n=13) studies estimate the cost of drug development from USD$92 million cash (USD$161 million capitalized) to USD$883.6 million cash (USD$1.8 billion capitalized) (Morgan et al., 2011). According to FDA, time to discover a new drugs takes an average of 10-12 years. Pre-clinical testing takes an average of 18 months (Range 1-3 years), clinical research and development takes an average of 5 years (Range 2-10 years) time. A new drug application to post marketing surveillance will take an average of 24 month (Range 2 month-10 years) (Dickson & Gagnon, 2009).
Drug repurposing is a recent increasing trend to find drugs for common and rare diseases to avoid high cost of new drug discovery and fasten the speed to identify new drugs (Pushpakom et al., 2019). Drug repositioning and similar terms have been a trending topic in literature and represent novel drug development strategies (Langedijk et al., 2015). Drug repositioning has several commercial and public health benefits. Aspirin is one of oldest drug was repositioned first as analgesic (1899), have been reposition for the second time to prevent the cancer (part. colorectal cancer) (Jourdan et al., 2020; Rothwell et al., 2011). Sildenafil was initially investigated as potential anti-hypertensive drug but later repositioned in the treatment of erectile dysfunction (Cavalla, 2017).
Bayesian design of experiment (B-DOE) is intended to develop from Bayes theorem which was developed by the English mathematician (Thomas Bayes). Thomas Bayes focused on how prior belief can be updated based on new evidence; a process now known as Bayesian inference, or Bayesian reasoning. Initial belief in the likelihood of a particular event or outcome are described as prior probabilities (for a hypothesis H we write this as P(H)); while updated beliefs in the light of new evidence E are posterior probabilities (written P(H|E) representing the conditional probability of H given E) (Bayes, 1763). Bayes’ theorem is a simple equation for calculating the posterior probability of a hypothesis H in terms of the prior probability, and the probability of the evidence conditional on H and its negation not H: